Vishal Kumar
Frontend DeveloperSenior Technical Lead at Paytm
Paytm
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Senior Technical Lead at Paytm
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Indian Institute Of Information Technology Allahabad
Bachelor’s Degree, Information Technology
January 1, 2012 – January 1, 2016
Netajee Defence Academy
High School, Intermediate
January 1, 2009 – January 1, 2011
Paytm
Senior Technical Lead
July 1, 2024 – Present
Paytm
Technical Lead
April 1, 2022 – July 1, 2024
Paytm
Senior Software Engineer
April 1, 2019 – March 1, 2022
Paytm
Software Engineer
April 1, 2018 – April 1, 2019
GoFro.com
Software Developer
July 1, 2016 – March 1, 2018
New Delhi Area, India
OnlineTyari.com
Software Developer Internship
January 1, 2016 – May 1, 2016
Comparative study on Email Spam Classifier using Data Mining technique.
November 1, 2015 – Present
To analyze the impact of classifier on detecting the spam or ham (non - spam) and evaluating the performance. Algorithm used were Multinomial Naive Bayes , K-Nearest Neighbor ,SVM classification . Data set : Ling Spam data
Hostel Management Web Portal
May 1, 2015 – Present
Focused on a web portal for managing and directing various students’ record related to their hostel activities. This web portal gives access to all students and their hostel wardens where they can search information related to each other. The Warden has been given all the update facilities while students have been given “read only” facilities. They can only search queries regarding any another student’s information. The portal also contains notices regarding day-to-day hostel activities.
Propositionalisation Strategy for Recommendar System
May 1, 2014 – Present
Focused in examining the impact of propositionalizational strategies on the application (Recommender System) which deals with Resource Description Framework (RDF) data. Usually binary features (e.g., true if a type or relation exists, false otherwise) or numerical features (e.g., counting the number of relations of a certain type) are used. Other variants e.g., computing the fraction of relations of a certain type are possible, but rarely used. In this Project three algorithms (k-NN,Random Forest,Bagging(J-48)) are applied to a dataset and accuracy is calculated and compared with each other for each feature type using propositionalizational strategies .
Cultural Fit Analysis
The candidate has a consistent career path within a single major company (Paytm) for a significant period, indicating loyalty and adaptability within a large organization. The personal projects show an interest in data science and web development, which, while not directly frontend, demonstrate a breadth of technical curiosity. The target role is 'Frontend Developer', but the experience is predominantly backend, which presents a significant mismatch. The lack of frontend-specific projects or skills in the professional experience suggests a potential gap in cultural fit for a dedicated frontend role.
Soft Skills & Operational Fit
The candidate's career progression at Paytm suggests strong operational fit and leadership potential, including mentoring and decision-making skills. However, specific soft skill demonstrations are not explicitly detailed in the provided data.